In order to contain all the relevant information of every scenario, the importance of scenario analysis or the transformation of early warning indication must be complicated and complex logic to determine the multiple combinations and strung into the database. In the normal state, considering the level of risk warning indication is quite complex and difficult to load. When problems arise, the increase in logic will not fully incorporated, and have to go through lengthy and time-consuming validation. Therefore, to rely on the database to show changes in risk early warning indications shall be highly dependent on the fast and powerful artificial intelligence to meet the need of solving. However, the current technology is still inadequate in this regards, analysts need to develop their own software programs to solve this problem.
Therefore, it is in need of a fault trees method of early warning indication for critical infrastructure protection.